Association and dissociation kinetics of colicin E3 and immunity protein 3: convergence of theory and experiment

Does Ionic Screening Lower Activation Barriers for Conformational Transitions in Proteins?

In this work, we investigated the kinetics of binding of hen egg-white lysozyme with tri- N-acetylglucosamine in aqueous solutions, at two values of pH, 3.2 and 11, as a function of ionic strength, by a stopped-flow method with tryptophyl fluorescence observation of the transients. We analyzed registered reaction progress curves by employing numerical integration of appropriate chemical master equations. We discriminated between several binding models and established that the process observed in experiments follows a two-step mechanism, composed of four elementary stages: diffusional formation of an encounter complex, dissociation of the encounter complex, conformational transition of the encounter complex to the final complex, and the reverse transformation, i.e., from the final complex to the encounter complex. We evaluated rate constants of these elementary stages and determined their dependencies on solution ionic strength. Regardless of solution pH, rate constants of both forward and reverse conformational transitions increase with an increasing ionic strength. This suggests that ionic screening of intramolecular electrostatic interactions may act to lower the activation barrier for conformational transition in proteins.

Forces Driving Chaperone Action

It is still unclear what molecular forces drive chaperone-mediated protein folding. Here, we obtain a detailed mechanistic understanding of the forces that dictate the four key steps of chaperone-client interaction: initial binding, complex stabilization, folding, and release. Contrary to the common belief that chaperones recognize unfolding intermediates by their hydrophobic nature, we discover that the model chaperone Spy uses long-range electrostatic interactions to rapidly bind to its unfolded client protein Im7. Short-range hydrophobic interactions follow, which serve to stabilize the complex. Hydrophobic collapse of the client protein then drives its folding. By burying hydrophobic residues in its core, the client's affinity to Spy decreases, which causes client release. By allowing the client to fold itself, Spy circumvents the need for client-specific folding instructions. This mechanism might help explain how chaperones can facilitate the folding of various unrelated proteins.

Regulation of JAK2 activation by Janus homology 2: evidence from molecular dynamics simulations

Janus kinase 2 (JAK2) is a protein tyrosine kinase implicated in signaling by specific members of the cytokine receptor family. Although it has been established that the JAK2 tyrosine kinase is negatively regulated by the JAK homology 2 (JH2) pseudokinase domain, the underlying mechanism of JH2 mediated regulation remains elusive. To elucidate the regulation of JAK2 kinase, we have built a structural model for the kinase and pseudokinase domains of JAK2. An asymmetric dimer is proposed, in which the kinase domain JH1 occupies a position where it could not be activated. We investigate the dynamic and energetic properties of the dimer by molecular dynamics simulation. JAK2 activation requires the two domains to be dissociated and rearranged in a form such that the JH1 kinase domain can adopt an active conformation. The significance of the above mechanism is emphasized by the finding that the activating V617F mutation destabilizes JH1-JH2 association in the proposed asymmetric dimer. Thus abrogation of the domain-domain interaction seems to be a possible first step for the structural rearrangement of the two domains, resulting in constitutive activation of JAK2 by the V617F mutation.

A unique bivalent binding and inhibition mechanism by the yatapoxvirus interleukin 18 binding protein

Interleukin 18 (IL18) is a cytokine that plays an important role in inflammation as well as host defense against microbes. Mammals encode a soluble inhibitor of IL18 termed IL18 binding protein (IL18BP) that modulates IL18 activity through a negative feedback mechanism. Many poxviruses encode homologous IL18BPs, which contribute to virulence. Previous structural and functional studies on IL18 and IL18BPs revealed an essential binding hot spot involving a lysine on IL18 and two aromatic residues on IL18BPs. The aromatic residues are conserved among the very diverse mammalian and poxviruses IL18BPs with the notable exception of yatapoxvirus IL18BPs, which lack a critical phenylalanine residue. To understand the mechanism by which yatapoxvirus IL18BPs neutralize IL18, we solved the crystal structure of the Yaba-Like Disease Virus (YLDV) IL18BP and IL18 complex at 1.75 Å resolution. YLDV-IL18BP forms a disulfide bonded homo-dimer engaging IL18 in a 2∶2 stoichiometry, in contrast to the 1∶1 complex of ectromelia virus (ECTV) IL18BP and IL18. Disruption of the dimer interface resulted in a functional monomer, however with a 3-fold decrease in binding affinity. The overall architecture of the YLDV-IL18BP:IL18 complex is similar to that observed in the ECTV-IL18BP:IL18 complex, despite lacking the critical lysine-phenylalanine interaction. Through structural and mutagenesis studies, contact residues that are unique to the YLDV-IL18BP:IL18 binding interface were identified, including Q67, P116 of YLDV-IL18BP and Y1, S105 and D110 of IL18. Overall, our studies show that YLDV-IL18BP is unique among the diverse family of mammalian and poxvirus IL-18BPs in that it uses a bivalent binding mode and a unique set of interacting residues for binding IL18. However, despite this extensive divergence, YLDV-IL18BP binds to the same surface of IL18 used by other IL18BPs, suggesting that all IL18BPs use a conserved inhibitory mechanism by blocking a putative receptor-binding site on IL18.

NMR structure of a heterodimeric SAM:SAM complex: characterization and manipulation of EphA2 binding reveal new cellular functions of SHIP2

The sterile alpha motif (SAM) for protein-protein interactions is encountered in over 200 proteins, but the structural basis for its interactions is just becoming clear. Here we solved the structure of the EphA2-SHIP2 SAM:SAM heterodimeric complex by use of NMR restraints from chemical shift perturbations, NOE and RDC experiments. Specific contacts between the protein surfaces differ significantly from a previous model and other SAM:SAM complexes. Molecular dynamics and docking simulations indicate fluctuations in the complex toward alternate, higher energy conformations. The interface suggests that EphA family members bind to SHIP2 SAM, whereas EphB members may not; correspondingly, we demonstrate binding of EphA1, but not of EphB2, to SHIP2. A variant of EphB2 SAM was designed that binds SHIP2. Functional characterization of a mutant EphA2 compromised in SHIP2 binding reveals two previously unrecognized functions of SHIP2 in suppressing ligand-induced activation of EphA2 and in promoting receptor coordinated chemotactic cell migration.

Measuring dissociation rate constants of protein complexes through subunit exchange: experimental design and theoretical modeling

Protein complexes are dynamic macromolecules that constantly dissociate into, and simultaneously are assembled from, free subunits. Dissociation rate constants, k_off, provide structural and functional information on protein complexes. However, because all existing methods for measuring k_off require high-quality purification and specific modifications of protein complexes, dissociation kinetics has only been studied for a small set of model complexes. Here, we propose a new method, called Metabolically-labeled Affinity-tagged Subunit Exchange (MASE), to measure k_off using metabolic stable isotope labeling, affinity purification and mass spectrometry. MASE is based on a subunit exchange process between an unlabeled affinity-tagged variant and a metabolically-labeled untagged variant of a complex. The subunit exchange process was modeled theoretically for a heterodimeric complex. The results showed that k_off determines, and hence can be estimated from, the observed rate of subunit exchange. This study provided the theoretical foundation for future experiments that can validate and apply the MASE method.

Predicting kinetic constants of protein-protein interactions based on structural properties

Elucidating kinetic processes of protein-protein interactions (PPI) helps to understand how basic building blocks affect overall behavior of living systems. In this study, we used structure-based properties to build predictive models for kinetic constants of PPI. A highly diverse PPI dataset, protein-protein kinetic interaction data and structures (PPKIDS), was built. PPKIDS contains 62 PPI with complex structures and kinetic constants measured experimentally. The influence of structural properties on kinetics of PPI was studied using 35 structure-based features, describing different aspects of complex structures. Linear models for the prediction of kinetic constants were built by fitting with selected subsets of structure-based features. The models gave correlation coefficients of 0.801, 0.732, and 0.770 for k(off), k(on), and K(d), respectively, in leave-one-out cross validations. The predictive models reported here use only protein complex structures as input and can be generally applied in PPI studies as well as systems biology modeling. Our study confirmed that different properties play different roles in the kinetic process of PPI. For example, k(on) was affected by overall structural features of complexes, such as the composition of secondary structures, the change of translational and rotational entropy, and the electrostatic interaction; while k(off) was determined by interfacial properties, such as number of contacted atom pairs per 100 Ų. This information provides useful hints for PPI design.

Rate theories for biologists

Some of the rate theories that are most useful for modeling biological processes are reviewed. By delving into some of the details and subtleties in the development of the theories, the review will hopefully help the reader gain a more than superficial perspective. Examples are presented to illustrate how rate theories can be used to generate insight at the microscopic level into biomolecular behaviors. An attempt is made to clear up a number of misconceptions in the literature regarding popular rate theories, including the appearance of Planck's constant in the transition-state theory and the Smoluchowski result as an upper limit for protein-protein and protein-DNA association rate constants. Future work in combining the implementation of rate theories through computer simulations with experimental probes of rate processes, and in modeling effects of intracellular environments so that theories can be used for generating rate constants for systems biology studies is particularly exciting.

Electron transfer from cytochrome c(2) to the reaction center: a transition state model for ionic strength effects due to neutral mutations

Interprotein electron transfer plays an important role in biological energy conversion. In this work, the electron transfer reaction between cytochrome c(2) (cyt) and the reaction center (RC) was studied to determine the mechanisms coupling association and electron transfer. Previous studies have shown that mutation of hydrophobic residues in the reaction interface, particularly Tyr L162, changes the binding affinity and rates of electron transfer at low ionic strengths. In this study, the effect of ionic strength on the second-order electron transfer rate constant, k(2), between cyt c(2) and native or mutant RCs was examined. Mutations of hydrophobic and hydrogen bonding residues caused k(2) to decrease more rapidly with an increase in ionic strength. This change is explained with a transition state model by a switch from a diffusion-limited reaction in native RCs, where electron transfer occurs upon each binding event, to a fast exchange reaction in the Tyr L162 mutant, where dissociation occurs before electron transfer and k(2) depends upon the equilibrium between bound and free protein complexes. The difference in ionic strength dependence is attributed to a smaller effect of ionic strength on the energy of the transition state compared to the bound state due to larger distances between charged residues in the transition state. This model explains the faster dissociation rate at higher ionic strengths that may assist rapid turnover that is important for biological function. These results provide a quantitative model for coupling protein association with electron transfer and elucidate the role of short-range interactions in determining the rate of electron transfer.

Dissection of the high rate constant for the binding of a ribotoxin to the ribosome

Restrictocin belongs to a family of site-specific ribonucleases that kill cells by inactivating the ribosome. The restrictocin-ribosome binding rate constant was observed to exceed 10(10) M(-1) s(-1). We have developed a transient-complex theory to model the binding rates of protein-protein and protein-RNA complexes. The theory predicts the rate constant as k(a) = k(a0) exp(-DeltaG(el)*/k(B)T), where k(a0) is the basal rate constant for reaching the transient complex, located at the outer boundary of the bound state, by random diffusion, and DeltaG(el)* is the average electrostatic interaction free energy of the transient complex. Here, we applied the transient-complex theory to dissect the high restrictocin-ribosome binding rate constant. We found that the binding rate of restrictocin to the isolated sarcin/ricin loop is electrostatically enhanced by approximately 300-fold, similar to results found in other protein-protein and protein-RNA complexes. The ribosome provides an additional 10,000-fold rate enhancement because of two synergistic mechanisms afforded by the distal regions of the ribosome. First, they provide additional electrostatic attraction with restrictocin. Second, they reposition the transient complex into a region where local electrostatic interactions of restrictocin with the sarcin/ricin loop are particularly favorable. Our calculations rationalize a host of experimental observations and identify a strategy for designing proteins that bind their targets with high speed.

Fast predictions of thermodynamics and kinetics of protein-protein recognition from structures: from molecular design to systems biology

The increasing call for an overall picture of the interactions between the components of a biological system that give rise to the observed function is often summarized by the expression systems biology. Both the interpretative and predictive capabilities of holistic models of biochemical systems, however, depend to a large extent on the level of physico-chemical knowledge of the individual molecular interactions making up the network. This review is focused on the structure-based quantitative characterization of protein-protein interactions, ubiquitous in any biochemical pathway. Recently developed, fast and effective computational methods are reviewed, which allow the assessment of kinetic and thermodynamic features of the association-dissociation processes of protein complexes, both in water soluble and membrane environments. The performance and the accuracy of fast and semi-empirical structure-based methods have reached comparable levels with respect to the classical and more elegant molecular simulations. Nevertheless, the broad accessibility and lower computational cost provide the former methods with the advantageous possibility to perform systems-level analyses including extensive in silico mutagenesis screenings and large-scale structural predictions of multiprotein complexes.

Electrostatic rate enhancement and transient complex of protein-protein association

The association of two proteins is bounded by the rate at which they, via diffusion, find each other while in appropriate relative orientations. Orientational constraints restrict this rate to approximately 10(5)-10(6) M(-1) s(-1). Proteins with higher association rates generally have complementary electrostatic surfaces; proteins with lower association rates generally are slowed down by conformational changes upon complex formation. Previous studies (Zhou, Biophys J 1997;73:2441-2445) have shown that electrostatic enhancement of the diffusion-limited association rate can be accurately modeled by $k_{\bf D}$ = $k_{D}0\ {exp} ( - \langle U_{el} \rangle;{\star}/k_{B} T),$ where k(D) and k(D0) are the rates in the presence and absence of electrostatic interactions, respectively, U(el) is the average electrostatic interaction energy in a "transient-complex" ensemble, and k(B)T is the thermal energy. The transient-complex ensemble separates the bound state from the unbound state. Predictions of the transient-complex theory on four protein complexes were found to agree well with the experiment when the electrostatic interaction energy was calculated with the linearized Poisson-Boltzmann (PB) equation (Alsallaq and Zhou, Structure 2007;15:215-224). Here we show that the agreement is further improved when the nonlinear PB equation is used. These predictions are obtained with the dielectric boundary defined as the protein van der Waals surface. When the dielectric boundary is instead specified as the molecular surface, electrostatic interactions in the transient complex become repulsive and are thus predicted to retard association. Together these results demonstrate that the transient-complex theory is predictive of electrostatic rate enhancement and can help parameterize PB calculations.

Prediction of salt and mutational effects on the association rate of U1A protein and U1 small nuclear RNA stem/loop II

We have developed a computational approach for predicting protein-protein association rates (Alsallaq and Zhou, Structure 2007, 15, 215). Here we expand the range of applicability of this approach to protein-RNA binding and report the first results for protein-RNA binding rates predicted from atomistic modeling. The system studied is the U1A protein and stem/loop II of the U1 small nuclear RNA. Experimentally it was observed that the binding rate is significantly reduced by increasing salt concentration while the dissociation changes little with salt concentration, and charges distant from the binding site make marginal contribution to the binding rate. These observations are rationalized. Moreover, predicted effects of salt and charge mutations are found to be in quantitative agreement with experimental results.

Do electrostatic interactions destabilize protein-nucleic acid binding?

The negatively charged phosphates of nucleic acids are often paired with positively charged residues upon binding proteins. It was thus counter-intuitive when previous Poisson-Boltzmann (PB) calculations gave positive energies from electrostatic interactions, meaning that they destabilize protein-nucleic acid binding. Our own PB calculations on protein-protein binding have shown that the sign and the magnitude of the electrostatic component are sensitive to the specification of the dielectric boundary in PB calculations. A popular choice for the boundary between the solute low dielectric and the solvent high dielectric is the molecular surface; an alternative is the van der Waals (vdW) surface. In line with results for protein-protein binding, in this article, we found that PB calculations with the molecular surface gave positive electrostatic interaction energies for two protein-RNA complexes, but the signs are reversed when the vdW surface was used. Therefore, whether destabilizing or stabilizing effects are predicted depends on the choice of the dielectric boundary. The two calculation protocols, however, yielded similar salt effects on the binding affinity. Effects of charge mutations differentiated the two calculation protocols; PB calculations with the vdW surface had smaller deviations overall from experimental data.

Prediction of protein-protein association rates from a transition-state theory

We recently developed a theory for the rates of protein-protein association. The theory is based on the concept of a transition state, which separates the bound state, with numerous short-range interactions but restricted translational and rotational freedom, and the unbound state, with, at most, a small number of interactions but expanded configurational freedom. When not accompanied by large-scale conformational changes, protein-protein association becomes diffusion limited. The association rate is then predicted as k(a)=k(a)(0)exp(-DeltaG(el)(double dagger)/k(B)T), where DeltaG(el)(double dagger) is the electrostatic interaction free energy in the transition state, k(a)(0) is the rate in the absence of electrostatic interactions, and k(B)T is thermal energy. Here, this transition-state theory is used to predict the association rates of four protein complexes. The predictions for the wild-type complexes and 23 mutants are found to agree closely with experimental data over wide ranges of ionic strength.

Structural systems biology: modelling protein interactions

Much of systems biology aims to predict the behaviour of biological systems on the basis of the set of molecules involved. Understanding the interactions between these molecules is therefore crucial to such efforts. Although many thousands of interactions are known, precise molecular details are available for only a tiny fraction of them. The difficulties that are involved in experimentally determining atomic structures for interacting proteins make predictive methods essential for progress. Structural details can ultimately turn abstract system representations into models that more accurately reflect biological reality.

How do biomolecular systems speed up and regulate rates?

The viability of a biological system depends upon careful regulation of the rates of various processes. These rates have limits imposed by intrinsic chemical or physical steps (e.g., diffusion). These limits can be expanded by interactions and dynamics of the biomolecules. For example, (a) a chemical reaction is catalyzed when its transition state is preferentially bound to an enzyme; (b) the folding of a protein molecule is speeded up by specific interactions within the transition-state ensemble and may be assisted by molecular chaperones; (c) the rate of specific binding of a protein molecule to a cellular target can be enhanced by mechanisms such as long-range electrostatic interactions, nonspecific binding and folding upon binding; (d) directional movement of motor proteins is generated by capturing favorable Brownian motion through intermolecular binding energy; and (e) conduction and selectivity of ions through membrane channels are controlled by interactions and the dynamics of channel proteins. Simple physical models are presented here to illustrate these processes and provide a unifying framework for understanding speed attainment and regulation in biomolecular systems.